Why do certain interfaces feel effortless while others feel exhausting? This paper proposes Timelines and Topographies as a conceptual framework to answer this question, reinterpreting interface design through the lens of human attention. We distinguish between timelines—a linear mode where the system serializes information to offload the cognitive cost of attentional control (e.g., social media feeds)—and topographies—a spatial mode where the system’s structural relations are directly presented to the user (e.g., folder hierarchies, canvas UIs). We apply this framework to analyze a wide spectrum of interfaces, ranging from classic desktop metaphors to modern Personal Information Management tools like Slack and Notion. Furthermore, we identify Large Language Models as bidirectional translators that bridge these modes by converting complex topographic structures into conversational timelines, and vice versa. Finally, we provide design guidelines for harnessing both modes, enabling interfaces that support fluid transitions between subjective timelines and objective topographies.

Text chat applications are an integral part of daily social and professional communication. However, messages sent over text chat applications do not convey vocal or nonverbal information from the sender, and detecting the emotional tone in text-only messages is challenging. In this paper, we explore the effects of speech balloon shapes on the sender-receiver agreement regarding the emotionality of a text message. We first investigated the relationship between the shape of a speech balloon and the emotionality of speech text in Japanese manga. Based on these results, we created a system that automatically generates speech balloons matching linear emotional arousal intensity by Auxiliary Classifier Generative Adversarial Networks (ACGAN). Our evaluation results from a controlled experiment suggested that the use of emotional speech balloons outperforms the use of emoticons in decreasing the differences between message senders’ and receivers’ perceptions about the level of emotional arousal in text messages.